CLASSIFYING OFFENSIVE LANGUAGE USE IN HATE SPEECHES OF K-POP FANS ON TWITTER

Siti Marina, Kamil and NurAthirah, Zulrushdi (2002) CLASSIFYING OFFENSIVE LANGUAGE USE IN HATE SPEECHES OF K-POP FANS ON TWITTER. In: Seoul International Conference on Linguistics (SICOL-2022), Sungkyunkwan University, South Korea., 11-12 August 2022, Online.

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Abstract

This study aims to categorize the offensive language identified within the hate speeches produced by K-pop fans on Twitter. It is a concern that the use of hate speeches among the fans would intensify cyberbullying. Nonetheless, little researches have been done on the categorization of offensive languages as previous researches have primarily relied on different data sets thus making it hard to do a comparison of different studies. There have been no benchmark data sets in categorizing offensive languages. A Natural Language Processing toolkit called “Orange” is used to extract tweets within a period with some requirements highlighted. The framework adopted from Wiegand et al. (2018) is used to categorize offensive language in this study. Findings have shown that from the 13,300 tweets that have been streamed, only 469 tweets are identified as hate speeches. Among all the 469 tweets, the insult category tops with 162 tweets, followed by the other category with 150 tweets, the profanity category with 135 tweets, and the abuse category with only 22 tweets. Contrary to what others might have presumed, K-pop fans are always associated with a negative nuance. In the desire to change this, the input in the analysis of hate speeches as well as the categorization of offensive languages gathered from this study has shown that even though the insult category tops the result, this study is not meant to generalize all K-pop fans. A lot of K-pop fans are aware of boundaries seeing that only 22 tweets are identified as abusive. This study will hopefully open up a new beginning to other researchers in this specific study.

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